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Detection of Near-Nulticollinearity through Centered and Noncentered Regression

Author

Listed:
  • Román Salmerón Gómez

    (Department of Quantitative Methods for Economics and Business, University of Granada, 18010 Granada, Spain)

  • Catalina García García

    (Department of Quantitative Methods for Economics and Business, University of Granada, 18010 Granada, Spain)

  • José García Pérez

    (Department of Economy and Company, University of Almería, 04120 Almería, Spain)

Abstract

This paper analyzes the diagnostic of near-multicollinearity in a multiple linear regression from auxiliary centered (with intercept) and noncentered (without intercept) regressions. From these auxiliary regressions, the centered and noncentered variance inflation factors (VIFs) are calculated. An expression is also presented that relates both of them. In addition, this paper analyzes why the VIF is not able to detect the relation between the intercept and the rest of the independent variables of an econometric model. At the same time, an analysis is also provided to determine how the auxiliary regression applied to calculate the VIF can be useful to detect this kind of multicollinearity.

Suggested Citation

  • Román Salmerón Gómez & Catalina García García & José García Pérez, 2020. "Detection of Near-Nulticollinearity through Centered and Noncentered Regression," Mathematics, MDPI, vol. 8(6), pages 1-17, June.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:6:p:931-:d:368403
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    References listed on IDEAS

    as
    1. David A. Belsley, 1988. "A Guide to Using the Collinearity Diagnostics," Boston College Working Papers in Economics 190, Boston College Department of Economics.
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    4. Chennamaneni, Pavan Rao & Echambadi, Raj & Hess, James D. & Syam, Niladri, 2016. "Diagnosing harmful collinearity in moderated regressions: A roadmap," International Journal of Research in Marketing, Elsevier, vol. 33(1), pages 172-182.
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    7. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    Full references (including those not matched with items on IDEAS)

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